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Machines Are Better Than Humans at Hiring the Best Employees

When an algorithm picks the candidate, they stay longer, new research finds.
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People want to believe they have good instincts, but when it comes to hiring, they can't best a computer. Hiring managers select worse job candidates than the ones recommended by an algorithm, new research from the National Bureau of Economic Research finds.

Looking across 15 companies and more than 300,000 hires in low-skill service-sector jobs, such as data entry and call center work, NBER researchers compared the tenure of employees who had been hired based on the algorithmic recommendations of a job test with that of people who'd been picked by a human. The test asked a variety of questions about technical skills, personality, cognitive skills, and fit for the job. The applicant's answers were run through an algorithm, which then spat out a recommendation: Green for high-potential candidates, yellow for moderate potential, and red for the lowest-rated.